Power Query & Power Pivot for Deep Analysis with Excel

Power Query & Power Pivot for Deep Analysis with Excel

Course Outline

Day 1: Power Query Essentials and Intermediate Techniques

Module 1: Introduction to Power Query

• Understanding the Role of Power Query in Data Preparation
• Navigating the Power Query Interface
• Key Use Cases of Power Query in Business Scenarios
• Differences Between Power Query in Excel and Power BI

Module 2: Data Transformation Basics

• Importing Data from Various Sources (Excel, CSV, SQL, Web, etc.)
• Data Cleaning Techniques: Removing Errors, Replacing Values
• Reordering Columns and Rows for Analysis
• Splitting and Merging Columns

Module 3: Advanced Data Transformation

• Advanced Filtering Techniques for Targeted Data Extraction
• Creating Custom Columns with Conditional Logic
• Using the Fill Down and Fill Up Features for Missing Data
• Advanced Grouping and Aggregating Techniques for Summarized Data

Module 4: Introduction to M Language

• Exploring the M Language Syntax and Structure
• Editing Queries Directly in the Advanced Editor
• Creating Custom Functions for Reusable Logic
• Common M Functions for Data Manipulation (e.g., Table.TransformColumns, Text.Combine)

Module 5: Case Studies and Practical Exercises

• Real-World Scenario: Preparing Sales Data for Reporting
• Combining Data from Multiple Files and Folders
• Practice Exercises with Provided Datasets
• Group Discussion on Common Data Challenges

Day 2: Power Pivot and Advanced Analytics

Module 6: Introduction to Power Pivot

• Overview of the Power Pivot Add-in: Activation and Setup
• Loading Data into the Power Pivot Data Model
• Understanding Table Relationships: One-to-One, One-to-Many
• Creating Hierarchies for Advanced Data Navigation

Module 7: DAX Fundamentals

• Overview of DAX: Syntax and Functions
• Understanding Row Context vs. Filter Context
• Creating Basic Calculated Columns and Measures
• Using Aggregation Functions (SUM, AVERAGE, COUNT, DISTINCTCOUNT)

Module 8: Advanced DAX Techniques

• Time Intelligence Functions: Calculating YTD, QTD, MTD, and Rolling Averages
• Advanced Logical Functions: SWITCH, IFERROR, CALCULATE
• Working with Iterative Functions: SUMX, AVERAGEX
• Troubleshooting DAX Formulas and Debugging Errors

Module 9: Optimizing Data Models

• Understanding the Importance of Star and Snowflake Schemas
• Best Practices for Efficient Data Models: Reducing File Size, Avoiding Duplicates
• Using the Diagram View for Relationship Management
• Performance Tuning: Analyzing and Optimizing Query Performance

Module 10: Advanced Analytics and Reporting

• Creating Slicers and Filters for Interactive Dashboards
• Designing Effective Power Pivot Reports with Visual Insights
• Using KPIs to Track and Display Key Business Metrics
• Integrating Power Query and Power Pivot for Dynamic Reporting

Module 11: Final Project and Review

• Hands-On Project: Building an Interactive Dashboard from Raw Data
• Applying Power Query and Power Pivot to Solve Business Problems
• Course Recap: Key Takeaways and Best Practices

These objectives aim to provide participants with a comprehensive understanding and practical skills in leveraging Power Query and Power Pivot for deep data analysis within Excel, preparing them to handle complex data challenges effectively.

The “Power Query & Power Pivot for Deep Analysis with Excel” course is designed to equip participants with advanced skills in data manipulation, analysis, and visualization using Excel’s powerful tools, Power Query and Power Pivot.

Participants will start by mastering Power Query, learning how to import data from various sources, clean and transform it efficiently. Moving into Power Pivot, they will delve into data modeling techniques, establishing relationships between tables, and creating calculated columns and measures using DAX expressions.

Throughout the course, emphasis will be placed on practical applications through hands-on exercises and real-world case studies, enabling participants to analyze complex datasets, generate insightful visualizations, and optimize performance for large-scale data scenarios.

By the end of the course, participants will have the tools and knowledge to confidently handle diverse data challenges, automate workflows, and enhance decision-making processes using Excel as a robust analytical platform.

To join the “Power Query & Power Pivot for Deep Analysis with Excel” course, participants should ideally have the following prerequisites:

1. Proficiency in Excel: Participants should be familiar with basic to intermediate Excel functionalities, including navigating through worksheets & using simple formulas and functions.
2. Understanding of Data Concepts: A basic understanding of fundamental data concepts such as tables, rows, columns, and data types is recommended.
3. Familiarity with Data Analysis: Some experience in data analysis tasks like sorting, filtering, and basic data manipulation within Excel will be beneficial.
4. Motivation to Learn: An eagerness to explore advanced data manipulation techniques and a willingness to engage in hands-on exercises and case studies throughout the course.

These prerequisites will ensure that participants can effectively engage with the course content, grasp advanced concepts in Power Query and Power Pivot, and apply their knowledge to real-world data analysis challenges using Excel.

The target audience for the “Power Query & Power Pivot for Deep Analysis with Excel” course includes professionals and individuals who work extensively with data in Excel and wish to deepen their analytical capabilities. This course is ideal for:

1. Data Analysts: Professionals who analyze and interpret data regularly and want to leverage advanced Excel tools for more efficient and insightful analysis.
2. Business Intelligence Professionals: Individuals involved in creating reports, dashboards, and data visualizations who seek to enhance their skills in data modeling and manipulation.
3. Financial Analysts: Those responsible for financial modeling, forecasting, and budgeting who want to streamline data handling and improve accuracy in their analyses.
4. Excel Power Users: Individuals already proficient in Excel who want to expand their toolkit with Power Query and Power Pivot for more sophisticated data transformations and analysis.
5. Managers and Decision-Makers: Leaders who rely on data-driven insights to make informed decisions and wish to improve their ability to extract and present meaningful insights from data.
6. IT Professionals and Consultants: Those tasked with managing and optimizing data workflows within organizations who want to leverage Excel’s capabilities for enhanced data management and reporting.

Overall, the course is suitable for anyone looking to advance their Excel skills specifically for data analysis, whether in business, finance, consulting, or other fields where data-driven decision-making is critical.